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This lecture explores the components of neuro robots, including sensors like cameras and microphones, motors such as server motors, legs, and arms, and an artificial brain model with simplified or detailed neurons. It delves into the translation of sensory signals into neural signals and the decoding of brain signals into motor signals. The lecture also compares these components to those found in actual animals, discussing perception, action, muscle movements, reflexes, rhythmic movements, and behaviors controlled by the brain. It highlights the closed loop between perception and action, emphasizing the brain's role in integrating sensory information, storing memories, and planning behaviors. The instructor addresses the mapping between sensors and the brain's computational parts, as well as the learning of different behaviors through adjusting connection weights in the brain's matrix.